Sensitivity, principal component and flux analysis applied to signal transduction: the case of epidermal growth factor mediated signaling.

Abstract

Novel high-throughput genomic and proteomic tools are allowing the integration of information from a range of biological assays into a single conceptual framework. This framework is often described as a network of biochemical reactions. We present strategies for the analysis of such networks. The direct differential method is described for the systematic evaluation of scaled sensitivity coefficients in reaction networks. Principal component analysis, based on an eigenvalue-eigenvector analysis of the scaled sensitivity coefficient matrix, is applied to rank individual reactions in the network based on their effect on system output. When combined with flux analysis, sensitivity analysis allows model reduction or simplification. Using epidermal growth factor (EGF) mediated signaling and trafficking as an example of signal transduction, we demonstrate that sensitivity analysis quantitatively reveals the dependence of dual-phosphorylated extracellular signal-regulated kinase (ERK) concentration on individual reaction rate constants. It predicts that EGF mediated reactions proceed primarily via an Shc-dependent pathway. Further, it suggests that receptor internalization and endosomal signaling are important features regulating signal output only at low EGF dosages and at later times.